Gospodarka Surowcami Mineralnymi - Mineral Resources Management

Coal is a cheap and accessible source of energy. However, the environmental costs associated with its exploitation and combustion are increasing. Burning coal generates large amounts of carbon dioxide. A gas that is a major contributor to global climate change.
Coal is a raw material used in various technologies (from energy to medicine) and is also the subject of scientific research. The directions for its use change over time. By tracing research trends related to coal, new research directions can be identified. Bibliometric analysis is used for this purpose, using a variety of data pertaining to scientific publications observed with the development of science. This method makes it possible to analyse networks of research, national and international, and to identify the internal logic of scientific development. This article aims to analyse research topics related to the word “coal” in the period covering 1950–2023. The article presents an analysis of publications indexed in the SCOPUS database. Publications that contained phrases related to search phrases containing the word “COAL” in the title, abstract, or keywords were included in the analysis. The dynamics of changes in the interest of coal researchers in subject areas, research areas, and countries were presented. On this basis, an attempt was made to identify future leading research topics related to coal and to identify limitations and barriers to the development of this research topic.

Diatomite rocks from the eastern part of the Polish outer Carpathians come in several varieties with different colour, compactness, amount of clay and sandy substance as well as the degree of silicification. One of them is dark grey blocky diatomite, present in the Jawornik deposit and characterised by average quality. During the tests, it was thermally calcined at temperatures from 300°C to 1,200°C in order to improve its functional properties. The results of observations regarding the changes that the rock and its components underwent under conditions of increasing temperature were presented. The results of thermal analysis, X-ray diffraction and tests of physical properties (i.e. density, water absorption and Vickers microhardness) of the rock were presented. Detailed observations of the rock’s mineral components were made using a scanning microscope. Their physical changes (e.g. cracks or signs of melting) and chemical transformations were described. It has been shown that during calcination, irreversible changes occur in the mineral composition and structure of diatomite. It was proven that for the discussed diatomite the optimal calcination temperature is 900°C, as it ensures the greatest increase in its open porosity by 11% and an almost threefold increase in its hardness. The chemical composition of diatomite also changes due to the combustion of the organic matter present in it and the resulting relative increase in the 1,200 content. Calcination improves the technological features of this variety of diatomite, making it similar to the best quality varieties found in this deposit.

An integrated process consisting of Li⁺ precipitation by Al(OH)₃, roasting, water leaching, evaporation, and Li₂CO₃ precipitation was used to recycle Li⁺ from the waste liquid of rock salt brine (0.099 g/L Li⁺). Waste liquid from roc salt brine was discharged wastewater after NaCl crystallization and the removal of impurities in the salt manufacturing plant of the good rock salt mine. The influences of Al³⁺/Li+ mole ratio, Na⁺/Al³⁺ mole ratio, precipitation temperature, and time on the recovery of Li⁺ were investigated during Li⁺ precipitation by Al(OH)₃ stage. The results showed that the optimal condition was Al³⁺/Li⁺ mole ratio = 2.5, Na⁺/Al³⁺ mole ratio = 2.2, precipitation

temperature of 60℃ (333.15 K) for more than 20 min, whose recovery of Li⁺ reached 97.25%. The thermodynamic analyses of the simulated Li⁺–Al⁺–Mg²⁺–Cl^––H₂O system were conducted to construct the potential-pH (φ-pH) diagrams. The results showed that the pH value should be located in the LiCl · 2Al(OH)₃ · 2H₂O salt region with no formation of Mg(OH)₂, which started at pH = ~6.5 and ended at pH from 10.09 to 8.55 as the temperature changed. Subsequently, the Li+precipitate was roasting for the transformation of insoluble LiCl · 2Al(OH)3 · xH₂O salt to soluble LiCl, followed by the water leaching to obtain the enriched Li⁺ solution (1.951 g/L Li⁺) with Li⁺ recovery of 85.52%. To

meet the requirement of Li₂CO₃ precipitation, the enriched Li+ solution was evaporated, and Na₂CO₃ was added to precipitate the Li₂CO₃ product after SO₄ ^2–, Ca²⁺, and Mg²⁺ removal. The total recovery of Li⁺ was 66.69% after the experimental process, and the purity of Li₂CO₃ product was 99.3%, which can be regarded as industrial-grade Li₂CO₃. In conclusion, the success in lithium recovery using the aluminum hydroxide precipitation method provided a new perspective for preparing Li₂CO₃ from the waste liquid of rock salt brine, which could be considered as a newly developing lithium resource to meet the dramatically increasing demand for lithium in new energy vehicle industry.

The iron and steel industry is a sector with very high energy consumption and also causing high emissions. It is difficult to imagine the development of modern sectors of the economy such as construction, transport or the machinery industry without the use of steel, so forecasts indicate that the demand for steel will increase in the future. Meanwhile, environmental concerns and concerns about climate change are growing, so the iron and steel industry faces a serious challenge related to reducing its emissions in order to achieve the goal set in the Paris Agreement, and this is even more true for this industry in the European Union. Currently, the most popular technology for steel production is the blast furnace process – basic oxygen furnace (BF-BOF). This technology requires the use of coal, which is a source of emissions, so a radical technological change is needed. Decarbonising the steel industry requires changing from coal-based metallurgy to hydrogen-based and electricity-based metallurgy. Changing from primary to secondary steel production (using scrap steel) improves the situation but is not a solution to meet growing demand. There are two main technology paths that can achieve significant CO₂ reduction. The first is Smart Carbon Usage (SCU), which is based on the gradual reduction of coal consumption, including the use of by-product gases for further conversion into valuable products. The second emerging technology path is Carbon Direct Avoidance (CDA). These and other developing methods of low-emission or zero-emission metallurgy are discussed in the article. Unfortunately, some of these methods are not mature and their final commercialisation requires overcoming a number of problems.

To meet the requirements of the image processing process on image quality, as the ore image contains Gaussian noise, pepper noise, Rayleigh noise, and other kinds of mixed noise is easy to destroy the real information of the image combined with the advantages of wavelet and non-local mean filtering, a new wavelet + non-local mean (NL-means) fusion denoising algorithm is proposed. Taking the ore image with mixed noise obtained from a mine as the research object, the wavelet function is used to carry out a two-dimensional wavelet transform on the filled image, separating the high and low-frequency information, setting the threshold vector to deal with the high-frequency wavelet coefficients, inverting the transform to get the first reconstructed image, followed by the second inverse transform. Then, the second reconstructed image is subjected to NL-mean denoising to remove the complex mixed noise in the ore image to the maximum extent. The experimental results show that the noise reduction performance of the fusion denoising algorithm has a greater improvement compared with the single filter and several other fusion algorithms. The peak signal-to-noise ratio of the denoised image is 31.0181dB. The structural similarity is 0.59913, which is 15.7584dB and 0.45241, respectively, compared with that before denoising. It has an obvious effect on the removal of the mixed noise in the ore image, which provides strong technical support to improve the noise removal of the ore image.

Ore particle size information is an important basis for mining enterprises to regulate crushing parameters, due to the complex and harsh environment during the acquisition of ore images on the conveyor belt, resulting in the existence of a variety of composite noise interference in the motion target image, the surface texture characteristics of the ore and the edge of the fuzzy and other problems, thus affecting the effective acquisition of ore particle size information. To address the above issues, an image-denoising network based on global and local feature extraction and an edge enhancement algorithm for texture feature weakening is proposed. The denoising network consists of a shallow local feature extraction module and a Transformer-based U-Net global feature extraction module, which aims to combine the powerful global modeling capability of the Transformer with the local modeling advantage of convolutional network, and reconstructs the image resolution through the dual up-sampling structure, to realize the accurate output of contextual detail information. A texture weakening method based on wavelet transform and fast non-local averaging is proposed to smooth the image and weaken the texture characteristics of the ore surface, and edge sharpening is combined with Bilateral- USMR to enhance the edges of the ore particles to realize the preprocessing of the ore image. The preprocessing results were objectively evaluated and experimentally verified. The results show that the image preprocessing method improves the accuracy of image segmentation and the applicability of the ore particle size measurement technology in complex environments.

At the ore crushing site, the crushed ore must be washed to remove sediment, and the washing step puts the detected ore in a watery environment, resulting in the presence of reflective areas in the image of watery ore particles. Aiming at the problem of mis-segmentation of ore images due to the masking of ore feature information by the reflective area, an improved Pix2PixGAN model is proposed to solve the problem of removing water and repairing the reflective area in watery ore images. The ResNet network with good stability is used to comprehensively extract the features of watery ore images, improve the stability of network training, introduce the structural similarity loss function, and update the network parameters by minimising the structural similarity loss value to reduce the structural differences between the reconstructed image and the real image. The experimental results show that the improved Pix2PixGAN model compares with the Pix2PixGAN and CycleGAN models; the watery ore image removes the water image reflection restoration better and, at the same time, improves the structural edge clarity of the generated dry ore particle image. The PSNR and SSIM evaluation metrics are improved by 8.8 and 1.28%, respectively, further verifying the effectiveness of the improved algorithm. This innovative approach provides a feasible solution for image processing at the ore-crushing site. It is of great significance for the subsequent enhancement of image recognition, segmentation, and reduction of misjudgment.

Closing coal mines in Poland is an important part of the energy transition aimed at reducing greenhouse gas emissions and meeting climate commitments. These decisions are particularly important in mining regions such as Silesia, where the mining industry is the main pillar of the economy. Given the gradual closure of mines and the reduction of employment in the mining sector, there is a need to analyse the migration of workers and their potential adaptation to the labour market. This paper aims to examine the impact of mine closures on the employment structure of the national economy using the input-output method. The analysis includes a decomposition of input-output tables (TPMD), in which branches such as thermal coal, coking coal, and lignite were distinguished. This has made it possible to precisely track economic flows between subsectors of the economy and identify which sectors are most vulnerable to the negative effects of reduced coal mining in Poland. The analysis also shows how a change in coal mining may affect related sectors such as energy, transport, and steel, increasing the need for structural adjustments. In particular, the article focuses on possible scenarios for the migration of workers from the closing mines and their re-deployment. Various coal reduction (WR) variants are considered, including WR25%, WR50%, WR75%, and WR100%, reflecting scenarios of declining domestic production. The paper also considers the possible substitution of domestic coal with imported raw materials (WS). The article concludes by identifying the most important conclusions.

The article presents a methodological approach that encompasses the conceptualisation of a design idea and the implementation of an information technology (IT)-based solution to support models developed for energy mix management. It identifies the key elements that influence the definition and subsequent creation of an IT solution, focusing on processes that reflect both the demand (coal demand) and supply sides.
In terms of the supply side, the IT solution will be equipped with planning information:

• Regarding minable resources, including general data on the resources currently held and the
  planned annual resources to be mined (qualitative data will not be included)
• The mining plans for each mine are accompanied by qualitative data (data that are standardised to ensure the quality of the production data collected.

In addition to mining plans, the supply side will have up-to-date information on coal already mined. This information will be presented in quantitative and qualitative terms at various stages of the product life cycle, which begins with the mining of raw coal and ends with the formation of a finished product that can be sold and transported to the customer.

The article indicates the key elements that must be precisely defined for the correct definition of processes on the demand side and the supply side, and in what order actions should be taken by IT specialists so that this solution fully satisfies the teams managing the processes dynamically.

This article aims to examine the level of ESG culture in Polish enterprises and indicate premises for implementation in the mining industry. The publication conducts a multi-criteria analysis of literature regarding companies’ approaches to ESG standards. The study focuses on shaping organisational culture by utilising knowledge management tools. The actual level of ESG culture among respondents was obtained through a survey. Survey results for individual groups are presented in comprehensive and averaged radar charts. The sample included employees from small, medium, and large companies, considering their tenure and the industry in which the enterprise operates. The pilot study enabled drawing many constructive conclusions. However, noticeable significant gaps in ESG-compliant organisational culture were observed. Companies primarily focus on their core activities, neglecting socially significant values and building additional employee bonds. Through the analysis of survey data, guidelines for implementing ESG reporting in specific areas were developed. Potential solutions to problematic issues for enterprises were also identified. The research has significant potential, and expanding the scope could directly impact the quality of reporting and the development of enterprises including entities in the mining industry.